Analysis of cfDNA fragmentomics metrics and commercial targeted sequencing panels

Kyle T. Helzer, Marina N. Sharifi, Jamie M. Sperger, Matthew R. Chrostek, Matthew L. Bootsma, Shannon R. Reese, Amy Taylor, Katie R. Kaufmann, Hannah Krause, Jennifer Schehr, Nan Sethakorn, David Kosoff, Christos E. Kyriakopoulos, Michael Bassetti, Grace Blitzer, John Floberg, Martin Sjöström, Andrew J. Armstrong, Himisha Beltran, Rana R. McKay, Felix Y. Feng, Ruth O’Regan, Kari B. Wisinski, Hamid Emamekhoo, Alex W. Wyatt, Joshua M. Lang and Shuang G. Zhao ()
Additional contact information
Kyle T. Helzer: University of Wisconsin
Marina N. Sharifi: University of Wisconsin
Jamie M. Sperger: University of Wisconsin
Matthew R. Chrostek: University of Wisconsin
Matthew L. Bootsma: University of Wisconsin
Shannon R. Reese: University of Wisconsin
Amy Taylor: University of Wisconsin
Katie R. Kaufmann: University of Wisconsin
Hannah Krause: University of Wisconsin
Jennifer Schehr: University of Wisconsin
Nan Sethakorn: University of Wisconsin
David Kosoff: University of Wisconsin
Christos E. Kyriakopoulos: University of Wisconsin
Michael Bassetti: University of Wisconsin
Grace Blitzer: University of Wisconsin
John Floberg: University of Wisconsin
Martin Sjöström: Lund University
Andrew J. Armstrong: Duke University
Himisha Beltran: Dana-Farber Cancer Institute
Rana R. McKay: University of California San Diego
Felix Y. Feng: University of California San Francisco
Ruth O’Regan: University of Wisconsin
Kari B. Wisinski: University of Wisconsin
Hamid Emamekhoo: University of Wisconsin
Alex W. Wyatt: University of British Columbia
Joshua M. Lang: University of Wisconsin
Shuang G. Zhao: University of Wisconsin

Nature Communications, 2025, vol. 16, issue 1, 1-12

Abstract: Abstract Fragmentomics based analysis of cell-free DNA (cfDNA) has recently emerged as a method to infer epigenetic and transcriptional data. Many of these reports analyze whole genome sequencing (WGS) which is not readily available clinically. Targeted exon panels are used for clinical cfDNA variant calling. In this report, we conduct an investigation of multiple published fragmentomics methods for WGS, but on cancer exon panels. We find that strategies utilizing normalized depth metrics, as well as all exons present on the panel, generally allow for better prediction of cancer phenotypes across a range of tumor fractions, though other metrics work particularly well in specific applications. Additionally, genes from commercial clinical targeted sequencing panels could be similarly employed for cancer phenotyping with a minimal decrease in performance despite their smaller genomic coverage. These results suggest that fragmentomics-based analysis of cfDNA can utilize targeted sequencing panels and does not necessarily require additional WGS.

Date: 2025
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DOI: 10.1038/s41467-025-64153-z

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